{"title":"泄漏流:识别通过加密802.11n连接传输的可变比特率DASH视频","authors":"Andrew Reed, Benjamin Klimkowski","doi":"10.1109/CCNC.2016.7444944","DOIUrl":null,"url":null,"abstract":"In recent years, Dynamic Adaptive Streaming over HTTP (DASH) has become the primary method to deliver video on the Internet, with Netflix currently leading the industry. Thus, any method to determine the content of a wireless Netflix stream presents a potential privacy concern for the entire DASH industry. In this paper, we demonstrate that it is possible to identify the Netflix video being streamed over an encrypted 802.11n connection with high accuracy in less than five minutes. Moreover, our technique works in scenarios where it is difficult to capture data frames due to a wireless access point's use of enhancements such as beamforming and multi-input/multi-output transmission.","PeriodicalId":399247,"journal":{"name":"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)","volume":"06 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Leaky streams: Identifying variable bitrate DASH videos streamed over encrypted 802.11n connections\",\"authors\":\"Andrew Reed, Benjamin Klimkowski\",\"doi\":\"10.1109/CCNC.2016.7444944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, Dynamic Adaptive Streaming over HTTP (DASH) has become the primary method to deliver video on the Internet, with Netflix currently leading the industry. Thus, any method to determine the content of a wireless Netflix stream presents a potential privacy concern for the entire DASH industry. In this paper, we demonstrate that it is possible to identify the Netflix video being streamed over an encrypted 802.11n connection with high accuracy in less than five minutes. Moreover, our technique works in scenarios where it is difficult to capture data frames due to a wireless access point's use of enhancements such as beamforming and multi-input/multi-output transmission.\",\"PeriodicalId\":399247,\"journal\":{\"name\":\"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)\",\"volume\":\"06 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCNC.2016.7444944\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC.2016.7444944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35
摘要
近年来,基于HTTP的动态自适应流媒体(Dynamic Adaptive Streaming over HTTP, DASH)已经成为在互联网上传输视频的主要方法,其中Netflix目前处于行业领先地位。因此,任何确定无线Netflix流内容的方法都会给整个DASH行业带来潜在的隐私问题。在本文中,我们证明了在不到五分钟的时间内以高精度识别通过加密802.11n连接流式传输的Netflix视频是可能的。此外,我们的技术适用于由于无线接入点使用波束成形和多输入/多输出传输等增强功能而难以捕获数据帧的情况。
In recent years, Dynamic Adaptive Streaming over HTTP (DASH) has become the primary method to deliver video on the Internet, with Netflix currently leading the industry. Thus, any method to determine the content of a wireless Netflix stream presents a potential privacy concern for the entire DASH industry. In this paper, we demonstrate that it is possible to identify the Netflix video being streamed over an encrypted 802.11n connection with high accuracy in less than five minutes. Moreover, our technique works in scenarios where it is difficult to capture data frames due to a wireless access point's use of enhancements such as beamforming and multi-input/multi-output transmission.